{
 "cells": [
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     "end_time": "2019-09-24T07:16:16.415409Z",
     "start_time": "2019-09-24T07:16:13.724606Z"
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       "      <td>江苏省</td>\n",
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       "      <td>2019/8/25 11:03:15</td>\n",
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       "      <td>CLEAR</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190806182754894140</td>\n",
       "      <td>2019/8/6 10:43:15</td>\n",
       "      <td>DUMIAO</td>\n",
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       "      <td>2019/8/6 10:45:17</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190807120418913168</td>\n",
       "      <td>2019/8/7 4:21:20</td>\n",
       "      <td>DUMIAO</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2019/9/8 2:39:29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190807124353915314</td>\n",
       "      <td>2019/8/7 5:04:23</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 2:39:25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190805114246830283</td>\n",
       "      <td>2019/8/5 4:10:08</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/10 1:37:20</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190805174608852049</td>\n",
       "      <td>2019/8/5 10:05:41</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/9 2:11:07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190810113741145073</td>\n",
       "      <td>2019/8/10 4:04:19</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 2:40:10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190809152753112528</td>\n",
       "      <td>2019/8/9 7:34:35</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 1:17:50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190809153415113096</td>\n",
       "      <td>2019/8/9 7:43:44</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 2:39:54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190809105535994587</td>\n",
       "      <td>2019/8/9 3:29:25</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 1:18:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190810104437140309</td>\n",
       "      <td>2019/8/10 3:02:00</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 6:23:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190808164225973236</td>\n",
       "      <td>2019/8/8 9:01:57</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 6:22:33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190808102950949249</td>\n",
       "      <td>2019/8/8 2:58:20</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 3:04:37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190809102312991977</td>\n",
       "      <td>2019/8/9 2:33:55</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 6:23:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>20190809161307116054</td>\n",
       "      <td>2019/8/9 8:49:40</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/4 23:34:27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190810110619142352</td>\n",
       "      <td>2019/8/10 10:14:47</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 2:40:11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190810172243168882</td>\n",
       "      <td>2019/8/10 10:25:40</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 6:23:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190811142029199558</td>\n",
       "      <td>2019/8/11 6:37:03</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/4 0:08:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190811143554200628</td>\n",
       "      <td>2019/8/11 7:06:41</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 1:18:01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190811144349201072</td>\n",
       "      <td>2019/8/11 7:13:22</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>辽宁省</td>\n",
       "      <td>20190811120314192051</td>\n",
       "      <td>2019/8/11 5:29:58</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/9/8 4:45:47</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207670</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190608183042102271</td>\n",
       "      <td>2019/6/8 10:41:30</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/2 23:29:19</td>\n",
       "      <td>2019/8/3 0:31:31</td>\n",
       "      <td>2019/9/2 21:15:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207671</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190601182211725214</td>\n",
       "      <td>2019/6/1 10:37:17</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/1 10:57:14</td>\n",
       "      <td>2019/6/1 10:57:14</td>\n",
       "      <td>2019/9/5 12:44:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207672</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190430092639950432</td>\n",
       "      <td>2019/4/30 1:54:32</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>2019/5/8 2:15:46</td>\n",
       "      <td>2019/6/3 17:00:50</td>\n",
       "      <td>2019/7/3 13:15:37</td>\n",
       "      <td>2019/8/3 11:49:32</td>\n",
       "      <td>2019/9/3 13:49:35</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207673</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190501155104160373</td>\n",
       "      <td>2019/5/1 8:06:01</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/2 20:37:05</td>\n",
       "      <td>2019/7/3 2:11:39</td>\n",
       "      <td>2019/8/3 1:52:26</td>\n",
       "      <td>2019/9/2 23:52:23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207674</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190625214135835387</td>\n",
       "      <td>2019/6/25 13:55:03</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/8 4:16:03</td>\n",
       "      <td>2019/8/4 12:47:42</td>\n",
       "      <td>2019/9/4 10:12:42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207675</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190624110450762141</td>\n",
       "      <td>2019/6/24 3:42:27</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/24 3:43:35</td>\n",
       "      <td>2019/6/24 3:43:35</td>\n",
       "      <td>2019/9/4 15:12:55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207676</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190628145312946093</td>\n",
       "      <td>2019/6/28 7:59:54</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/8 4:16:32</td>\n",
       "      <td>2019/8/8 4:54:48</td>\n",
       "      <td>2019/9/9 11:56:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207677</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190624111837763276</td>\n",
       "      <td>2019/6/24 3:48:57</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/8 4:16:00</td>\n",
       "      <td>2019/8/3 21:38:40</td>\n",
       "      <td>2019/9/5 10:32:39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207678</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190524165522370346</td>\n",
       "      <td>2019/5/27 10:51:43</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 16:45:17</td>\n",
       "      <td>2019/7/3 12:44:52</td>\n",
       "      <td>2019/8/3 12:19:41</td>\n",
       "      <td>2019/9/3 13:57:51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207679</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190528095504510448</td>\n",
       "      <td>2019/5/28 2:29:03</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/7 3:05:57</td>\n",
       "      <td>2019/7/6 0:35:37</td>\n",
       "      <td>2019/8/7 0:32:44</td>\n",
       "      <td>2019/9/6 0:39:55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207680</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190526153935453548</td>\n",
       "      <td>2019/5/26 7:51:46</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:39:23</td>\n",
       "      <td>2019/7/8 4:15:29</td>\n",
       "      <td>2019/8/3 14:00:18</td>\n",
       "      <td>2019/9/7 9:31:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207681</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190526171029459987</td>\n",
       "      <td>2019/5/26 9:44:41</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:39:23</td>\n",
       "      <td>2019/7/8 4:15:30</td>\n",
       "      <td>2019/8/5 14:29:47</td>\n",
       "      <td>2019/9/8 1:14:51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207682</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190512093721651499</td>\n",
       "      <td>2019/5/12 1:49:32</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 17:18:46</td>\n",
       "      <td>2019/7/3 12:53:03</td>\n",
       "      <td>2019/8/3 12:04:29</td>\n",
       "      <td>2019/9/3 13:39:20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207683</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190514140923743112</td>\n",
       "      <td>2019/5/14 6:16:34</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/2 20:52:00</td>\n",
       "      <td>2019/7/3 2:28:57</td>\n",
       "      <td>2019/8/3 2:39:56</td>\n",
       "      <td>2019/9/2 23:11:59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207684</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190509152500542897</td>\n",
       "      <td>2019/5/9 7:34:35</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/5 16:45:51</td>\n",
       "      <td>2019/7/6 0:01:18</td>\n",
       "      <td>2019/8/6 5:39:26</td>\n",
       "      <td>2019/9/8 1:14:18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207685</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190505143717380752</td>\n",
       "      <td>2019/5/5 7:40:03</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 17:49:56</td>\n",
       "      <td>2019/7/3 14:27:28</td>\n",
       "      <td>2019/8/3 11:18:50</td>\n",
       "      <td>2019/9/3 14:14:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207686</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190505202105399822</td>\n",
       "      <td>2019/5/5 13:35:43</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:38:13</td>\n",
       "      <td>2019/7/6 14:33:49</td>\n",
       "      <td>2019/8/5 18:26:38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>OPEN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207687</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190503150012285032</td>\n",
       "      <td>2019/5/3 7:07:19</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 16:13:11</td>\n",
       "      <td>2019/7/3 12:44:12</td>\n",
       "      <td>2019/8/3 12:18:35</td>\n",
       "      <td>2019/9/3 14:28:31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207688</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190502185703248491</td>\n",
       "      <td>2019/5/2 11:23:52</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/6 1:49:11</td>\n",
       "      <td>2019/7/5 1:19:48</td>\n",
       "      <td>2019/8/5 1:26:15</td>\n",
       "      <td>2019/9/6 5:12:38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207689</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190506152438423207</td>\n",
       "      <td>2019/5/6 8:21:46</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 4:41:36</td>\n",
       "      <td>2019/7/4 0:54:18</td>\n",
       "      <td>2019/8/8 7:59:47</td>\n",
       "      <td>2019/9/2 22:54:48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207690</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190503165834296598</td>\n",
       "      <td>2019/5/3 9:23:53</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:38:21</td>\n",
       "      <td>2019/7/8 4:15:18</td>\n",
       "      <td>2019/8/8 1:03:54</td>\n",
       "      <td>2019/9/8 1:14:28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207691</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190423195455686941</td>\n",
       "      <td>2019/4/23 12:18:02</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>2019/5/3 10:03:26</td>\n",
       "      <td>2019/6/3 18:03:13</td>\n",
       "      <td>2019/7/3 15:05:33</td>\n",
       "      <td>2019/8/3 13:36:29</td>\n",
       "      <td>2019/9/3 14:28:51</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207692</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190423111442658657</td>\n",
       "      <td>2019/4/23 4:11:32</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>2019/5/5 19:39:13</td>\n",
       "      <td>2019/6/5 22:31:46</td>\n",
       "      <td>2019/7/6 16:58:56</td>\n",
       "      <td>2019/8/6 0:26:49</td>\n",
       "      <td>2019/9/5 15:23:00</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207693</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190424115344699499</td>\n",
       "      <td>2019/4/24 4:02:50</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>2019/5/2 19:01:03</td>\n",
       "      <td>2019/6/2 21:19:14</td>\n",
       "      <td>2019/7/3 2:16:30</td>\n",
       "      <td>2019/8/3 1:43:03</td>\n",
       "      <td>2019/9/2 23:48:26</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207694</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190422154128636241</td>\n",
       "      <td>2019/4/22 7:54:48</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/5/2 20:06:20</td>\n",
       "      <td>2019/6/2 20:50:44</td>\n",
       "      <td>2019/7/3 1:19:13</td>\n",
       "      <td>2019/8/3 1:48:43</td>\n",
       "      <td>2019/9/2 22:41:07</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207695</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190518172501962433</td>\n",
       "      <td>2019/5/18 9:41:04</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/2 19:27:14</td>\n",
       "      <td>2019/7/2 23:39:51</td>\n",
       "      <td>2019/8/3 0:32:19</td>\n",
       "      <td>2019/9/2 20:54:06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207696</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190519133935995812</td>\n",
       "      <td>2019/5/19 8:26:53</td>\n",
       "      <td>ZIZHUSHOUXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/3 16:33:33</td>\n",
       "      <td>2019/7/3 12:38:04</td>\n",
       "      <td>2019/8/3 12:55:36</td>\n",
       "      <td>2019/9/3 14:12:08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207697</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190516170222836355</td>\n",
       "      <td>2019/5/16 9:19:55</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/5 22:31:05</td>\n",
       "      <td>2019/7/6 16:46:27</td>\n",
       "      <td>2019/8/6 0:14:18</td>\n",
       "      <td>2019/9/5 15:21:48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207698</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190520121014139555</td>\n",
       "      <td>2019/5/20 4:38:10</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/6/8 1:39:04</td>\n",
       "      <td>2019/7/8 4:15:24</td>\n",
       "      <td>2019/8/5 13:18:30</td>\n",
       "      <td>2019/9/8 1:14:24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207699</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190414165416314395</td>\n",
       "      <td>2019/4/14 9:10:31</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/4/14 9:12:00</td>\n",
       "      <td>2019/4/14 9:12:00</td>\n",
       "      <td>2019/7/6 1:57:57</td>\n",
       "      <td>2019/8/5 9:49:17</td>\n",
       "      <td>2019/9/5 2:26:40</td>\n",
       "      <td>201905.0</td>\n",
       "      <td>201906.0</td>\n",
       "      <td>201907.0</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>207700 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ACCEPT_AREA_NAME            ACCOUNT_ID       COMPLETE_TIME  \\\n",
       "0                   江苏省  20190824192308836421  2019/8/24 11:51:34   \n",
       "1                   重庆市  20190822175909712306  2019/8/22 10:20:51   \n",
       "2                   广东省  20190825183011892326  2019/8/25 10:35:58   \n",
       "3                   浙江省  20190825205342898748  2019/8/25 13:02:02   \n",
       "4                   浙江省  20190823154133755956   2019/8/23 7:45:52   \n",
       "5                   浙江省  20190823161523759189   2019/8/23 8:25:43   \n",
       "6                   江苏省  20190823171701765541   2019/8/23 9:56:37   \n",
       "7                   江苏省  20190825083043842279   2019/8/25 0:47:57   \n",
       "8                   江苏省  20190825184430893050  2019/8/25 11:03:15   \n",
       "9                   广东省  20190805152252842434    2019/8/5 7:37:49   \n",
       "10                  四川省  20190806182754894140   2019/8/6 10:43:15   \n",
       "11             新疆维吾尔自治区  20190807120418913168    2019/8/7 4:21:20   \n",
       "12                  浙江省  20190807124353915314    2019/8/7 5:04:23   \n",
       "13                  浙江省  20190805114246830283    2019/8/5 4:10:08   \n",
       "14                  重庆市  20190805174608852049   2019/8/5 10:05:41   \n",
       "15             新疆维吾尔自治区  20190810113741145073   2019/8/10 4:04:19   \n",
       "16                  江苏省  20190809152753112528    2019/8/9 7:34:35   \n",
       "17             新疆维吾尔自治区  20190809153415113096    2019/8/9 7:43:44   \n",
       "18                  重庆市  20190809105535994587    2019/8/9 3:29:25   \n",
       "19                  四川省  20190810104437140309   2019/8/10 3:02:00   \n",
       "20             新疆维吾尔自治区  20190808164225973236    2019/8/8 9:01:57   \n",
       "21                  湖北省  20190808102950949249    2019/8/8 2:58:20   \n",
       "22                  浙江省  20190809102312991977    2019/8/9 2:33:55   \n",
       "23               内蒙古自治区  20190809161307116054    2019/8/9 8:49:40   \n",
       "24                  四川省  20190810110619142352  2019/8/10 10:14:47   \n",
       "25                  重庆市  20190810172243168882  2019/8/10 10:25:40   \n",
       "26                  江苏省  20190811142029199558   2019/8/11 6:37:03   \n",
       "27                  广东省  20190811143554200628   2019/8/11 7:06:41   \n",
       "28                  浙江省  20190811144349201072   2019/8/11 7:13:22   \n",
       "29                  辽宁省  20190811120314192051   2019/8/11 5:29:58   \n",
       "...                 ...                   ...                 ...   \n",
       "207670              江苏省  20190608183042102271   2019/6/8 10:41:30   \n",
       "207671              广东省  20190601182211725214   2019/6/1 10:37:17   \n",
       "207672              江苏省  20190430092639950432   2019/4/30 1:54:32   \n",
       "207673              江苏省  20190501155104160373    2019/5/1 8:06:01   \n",
       "207674              广东省  20190625214135835387  2019/6/25 13:55:03   \n",
       "207675              广东省  20190624110450762141   2019/6/24 3:42:27   \n",
       "207676              广东省  20190628145312946093   2019/6/28 7:59:54   \n",
       "207677              广东省  20190624111837763276   2019/6/24 3:48:57   \n",
       "207678              江苏省  20190524165522370346  2019/5/27 10:51:43   \n",
       "207679              重庆市  20190528095504510448   2019/5/28 2:29:03   \n",
       "207680              广东省  20190526153935453548   2019/5/26 7:51:46   \n",
       "207681              广东省  20190526171029459987   2019/5/26 9:44:41   \n",
       "207682              江苏省  20190512093721651499   2019/5/12 1:49:32   \n",
       "207683              江苏省  20190514140923743112   2019/5/14 6:16:34   \n",
       "207684              广东省  20190509152500542897    2019/5/9 7:34:35   \n",
       "207685              江苏省  20190505143717380752    2019/5/5 7:40:03   \n",
       "207686              广东省  20190505202105399822   2019/5/5 13:35:43   \n",
       "207687              江苏省  20190503150012285032    2019/5/3 7:07:19   \n",
       "207688              重庆市  20190502185703248491   2019/5/2 11:23:52   \n",
       "207689              江苏省  20190506152438423207    2019/5/6 8:21:46   \n",
       "207690              江苏省  20190503165834296598    2019/5/3 9:23:53   \n",
       "207691              江苏省  20190423195455686941  2019/4/23 12:18:02   \n",
       "207692              广东省  20190423111442658657   2019/4/23 4:11:32   \n",
       "207693              江苏省  20190424115344699499   2019/4/24 4:02:50   \n",
       "207694              江苏省  20190422154128636241   2019/4/22 7:54:48   \n",
       "207695              江苏省  20190518172501962433   2019/5/18 9:41:04   \n",
       "207696              江苏省  20190519133935995812   2019/5/19 8:26:53   \n",
       "207697              广东省  20190516170222836355   2019/5/16 9:19:55   \n",
       "207698              广东省  20190520121014139555   2019/5/20 4:38:10   \n",
       "207699              重庆市  20190414165416314395   2019/4/14 9:10:31   \n",
       "\n",
       "              CREDIT_BY        REPAY_TIME5        REPAY_TIME6  \\\n",
       "0                WEIXIN                NaN                NaN   \n",
       "1                WEIXIN                NaN                NaN   \n",
       "2                YUEBAO                NaN                NaN   \n",
       "3                YUEBAO                NaN                NaN   \n",
       "4                YUEBAO                NaN                NaN   \n",
       "5                DUMIAO                NaN                NaN   \n",
       "6                WEIXIN                NaN                NaN   \n",
       "7       TIANCHENGRONGZU                NaN                NaN   \n",
       "8       TIANCHENGRONGZU                NaN                NaN   \n",
       "9       TIANCHENGRONGZU                NaN                NaN   \n",
       "10               DUMIAO                NaN                NaN   \n",
       "11               DUMIAO                NaN                NaN   \n",
       "12               DUMIAO                NaN                NaN   \n",
       "13               DUMIAO                NaN                NaN   \n",
       "14               WEIXIN                NaN                NaN   \n",
       "15               DUMIAO                NaN                NaN   \n",
       "16               WEIXIN                NaN                NaN   \n",
       "17               DUMIAO                NaN                NaN   \n",
       "18               WEIXIN                NaN                NaN   \n",
       "19      TIANCHENGRONGZU                NaN                NaN   \n",
       "20      TIANCHENGRONGZU                NaN                NaN   \n",
       "21      TIANCHENGRONGZU                NaN                NaN   \n",
       "22      TIANCHENGRONGZU                NaN                NaN   \n",
       "23             ZHAOLIAN                NaN                NaN   \n",
       "24               DUMIAO                NaN                NaN   \n",
       "25      TIANCHENGRONGZU                NaN                NaN   \n",
       "26               WEIXIN                NaN                NaN   \n",
       "27               WEIXIN                NaN                NaN   \n",
       "28               DUMIAO                NaN                NaN   \n",
       "29             ZHAOLIAN                NaN                NaN   \n",
       "...                 ...                ...                ...   \n",
       "207670           WEIXIN                NaN                NaN   \n",
       "207671     ZIZHUSHOUXIN                NaN                NaN   \n",
       "207672         ZHAOLIAN   2019/5/8 2:15:46  2019/6/3 17:00:50   \n",
       "207673           WEIXIN                NaN  2019/6/2 20:37:05   \n",
       "207674           WEIXIN                NaN                NaN   \n",
       "207675           WEIXIN                NaN                NaN   \n",
       "207676     ZIZHUSHOUXIN                NaN                NaN   \n",
       "207677           WEIXIN                NaN                NaN   \n",
       "207678     ZIZHUSHOUXIN                NaN  2019/6/3 16:45:17   \n",
       "207679           WEIXIN                NaN   2019/6/7 3:05:57   \n",
       "207680           WEIXIN                NaN   2019/6/8 1:39:23   \n",
       "207681           WEIXIN                NaN   2019/6/8 1:39:23   \n",
       "207682         ZHAOLIAN                NaN  2019/6/3 17:18:46   \n",
       "207683   MASHANGXIAOJIN                NaN  2019/6/2 20:52:00   \n",
       "207684           WEIXIN                NaN  2019/6/5 16:45:51   \n",
       "207685         ZHAOLIAN                NaN  2019/6/3 17:49:56   \n",
       "207686           WEIXIN                NaN   2019/6/8 1:38:13   \n",
       "207687   MASHANGXIAOJIN                NaN  2019/6/3 16:13:11   \n",
       "207688     ZIZHUSHOUXIN                NaN   2019/6/6 1:49:11   \n",
       "207689   MASHANGXIAOJIN                NaN   2019/6/8 4:41:36   \n",
       "207690           WEIXIN                NaN   2019/6/8 1:38:21   \n",
       "207691         ZHAOLIAN  2019/5/3 10:03:26  2019/6/3 18:03:13   \n",
       "207692     ZIZHUSHOUXIN  2019/5/5 19:39:13  2019/6/5 22:31:46   \n",
       "207693     ZIZHUSHOUXIN  2019/5/2 19:01:03  2019/6/2 21:19:14   \n",
       "207694           WEIXIN  2019/5/2 20:06:20  2019/6/2 20:50:44   \n",
       "207695           WEIXIN                NaN  2019/6/2 19:27:14   \n",
       "207696     ZIZHUSHOUXIN                NaN  2019/6/3 16:33:33   \n",
       "207697   MASHANGXIAOJIN                NaN  2019/6/5 22:31:05   \n",
       "207698           WEIXIN                NaN   2019/6/8 1:39:04   \n",
       "207699           WEIXIN  2019/4/14 9:12:00  2019/4/14 9:12:00   \n",
       "\n",
       "              REPAY_TIME7        REPAY_TIME8        REPAY_TIME9   SEASON5  \\\n",
       "0                     NaN                NaN  2019/9/3 15:19:38       NaN   \n",
       "1                     NaN                NaN   2019/9/8 1:19:17       NaN   \n",
       "2                     NaN                NaN   2019/9/8 6:34:49       NaN   \n",
       "3                     NaN                NaN                NaN       NaN   \n",
       "4                     NaN                NaN   2019/9/9 2:20:43       NaN   \n",
       "5                     NaN                NaN   2019/9/8 2:44:02       NaN   \n",
       "6                     NaN                NaN  2019/9/3 17:29:03       NaN   \n",
       "7                     NaN                NaN   2019/9/8 6:28:30       NaN   \n",
       "8                     NaN                NaN   2019/9/8 6:28:42       NaN   \n",
       "9                     NaN                NaN  2019/9/5 12:53:48       NaN   \n",
       "10                    NaN                NaN  2019/8/6 10:45:17       NaN   \n",
       "11                    NaN                NaN   2019/9/8 2:39:29       NaN   \n",
       "12                    NaN                NaN   2019/9/8 2:39:25       NaN   \n",
       "13                    NaN                NaN  2019/9/10 1:37:20       NaN   \n",
       "14                    NaN                NaN   2019/9/9 2:11:07       NaN   \n",
       "15                    NaN                NaN   2019/9/8 2:40:10       NaN   \n",
       "16                    NaN                NaN   2019/9/8 1:17:50       NaN   \n",
       "17                    NaN                NaN   2019/9/8 2:39:54       NaN   \n",
       "18                    NaN                NaN   2019/9/8 1:18:32       NaN   \n",
       "19                    NaN                NaN   2019/9/8 6:23:03       NaN   \n",
       "20                    NaN                NaN   2019/9/8 6:22:33       NaN   \n",
       "21                    NaN                NaN   2019/8/8 3:04:37       NaN   \n",
       "22                    NaN                NaN   2019/9/8 6:23:00       NaN   \n",
       "23                    NaN                NaN  2019/9/4 23:34:27       NaN   \n",
       "24                    NaN                NaN   2019/9/8 2:40:11       NaN   \n",
       "25                    NaN                NaN   2019/9/8 6:23:21       NaN   \n",
       "26                    NaN                NaN   2019/9/4 0:08:03       NaN   \n",
       "27                    NaN                NaN   2019/9/8 1:18:01       NaN   \n",
       "28                    NaN                NaN                NaN       NaN   \n",
       "29                    NaN                NaN   2019/9/8 4:45:47       NaN   \n",
       "...                   ...                ...                ...       ...   \n",
       "207670  2019/7/2 23:29:19   2019/8/3 0:31:31  2019/9/2 21:15:21       NaN   \n",
       "207671  2019/6/1 10:57:14  2019/6/1 10:57:14  2019/9/5 12:44:57       NaN   \n",
       "207672  2019/7/3 13:15:37  2019/8/3 11:49:32  2019/9/3 13:49:35  201905.0   \n",
       "207673   2019/7/3 2:11:39   2019/8/3 1:52:26  2019/9/2 23:52:23       NaN   \n",
       "207674   2019/7/8 4:16:03  2019/8/4 12:47:42  2019/9/4 10:12:42       NaN   \n",
       "207675  2019/6/24 3:43:35  2019/6/24 3:43:35  2019/9/4 15:12:55       NaN   \n",
       "207676   2019/7/8 4:16:32   2019/8/8 4:54:48  2019/9/9 11:56:16       NaN   \n",
       "207677   2019/7/8 4:16:00  2019/8/3 21:38:40  2019/9/5 10:32:39       NaN   \n",
       "207678  2019/7/3 12:44:52  2019/8/3 12:19:41  2019/9/3 13:57:51       NaN   \n",
       "207679   2019/7/6 0:35:37   2019/8/7 0:32:44   2019/9/6 0:39:55       NaN   \n",
       "207680   2019/7/8 4:15:29  2019/8/3 14:00:18   2019/9/7 9:31:17       NaN   \n",
       "207681   2019/7/8 4:15:30  2019/8/5 14:29:47   2019/9/8 1:14:51       NaN   \n",
       "207682  2019/7/3 12:53:03  2019/8/3 12:04:29  2019/9/3 13:39:20       NaN   \n",
       "207683   2019/7/3 2:28:57   2019/8/3 2:39:56  2019/9/2 23:11:59       NaN   \n",
       "207684   2019/7/6 0:01:18   2019/8/6 5:39:26   2019/9/8 1:14:18       NaN   \n",
       "207685  2019/7/3 14:27:28  2019/8/3 11:18:50  2019/9/3 14:14:30       NaN   \n",
       "207686  2019/7/6 14:33:49  2019/8/5 18:26:38                NaN       NaN   \n",
       "207687  2019/7/3 12:44:12  2019/8/3 12:18:35  2019/9/3 14:28:31       NaN   \n",
       "207688   2019/7/5 1:19:48   2019/8/5 1:26:15   2019/9/6 5:12:38       NaN   \n",
       "207689   2019/7/4 0:54:18   2019/8/8 7:59:47  2019/9/2 22:54:48       NaN   \n",
       "207690   2019/7/8 4:15:18   2019/8/8 1:03:54   2019/9/8 1:14:28       NaN   \n",
       "207691  2019/7/3 15:05:33  2019/8/3 13:36:29  2019/9/3 14:28:51  201905.0   \n",
       "207692  2019/7/6 16:58:56   2019/8/6 0:26:49  2019/9/5 15:23:00  201905.0   \n",
       "207693   2019/7/3 2:16:30   2019/8/3 1:43:03  2019/9/2 23:48:26  201905.0   \n",
       "207694   2019/7/3 1:19:13   2019/8/3 1:48:43  2019/9/2 22:41:07  201905.0   \n",
       "207695  2019/7/2 23:39:51   2019/8/3 0:32:19  2019/9/2 20:54:06       NaN   \n",
       "207696  2019/7/3 12:38:04  2019/8/3 12:55:36  2019/9/3 14:12:08       NaN   \n",
       "207697  2019/7/6 16:46:27   2019/8/6 0:14:18  2019/9/5 15:21:48       NaN   \n",
       "207698   2019/7/8 4:15:24  2019/8/5 13:18:30   2019/9/8 1:14:24       NaN   \n",
       "207699   2019/7/6 1:57:57   2019/8/5 9:49:17   2019/9/5 2:26:40  201905.0   \n",
       "\n",
       "         SEASON6   SEASON7   SEASON8 STATUS5 STATUS6 STATUS7 STATUS8 STATUS9  \\\n",
       "0            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "1            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "2            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "3            NaN       NaN       NaN     NaN     NaN     NaN     NaN    OPEN   \n",
       "4            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "5            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "6            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "7            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "8            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "9            NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "10           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "11           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "12           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "13           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "14           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "15           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "16           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "17           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "18           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "19           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "20           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "21           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "22           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "23           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "24           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "25           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "26           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "27           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "28           NaN       NaN       NaN     NaN     NaN     NaN     NaN    OPEN   \n",
       "29           NaN       NaN       NaN     NaN     NaN     NaN     NaN   CLEAR   \n",
       "...          ...       ...       ...     ...     ...     ...     ...     ...   \n",
       "207670       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207671       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207672  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207673  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207674       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207675       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207676       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207677       NaN  201907.0  201908.0     NaN     NaN   CLEAR   CLEAR   CLEAR   \n",
       "207678  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207679  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207680  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207681  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207682  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207683  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207684  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207685  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207686  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR    OPEN   \n",
       "207687  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207688  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207689  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207690  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207691  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207692  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207693  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207694  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207695  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207696  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207697  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207698  201906.0  201907.0  201908.0     NaN   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "207699  201906.0  201907.0  201908.0   CLEAR   CLEAR   CLEAR   CLEAR   CLEAR   \n",
       "\n",
       "        USER_TYPE  \n",
       "0               2  \n",
       "1               2  \n",
       "2              10  \n",
       "3              10  \n",
       "4              10  \n",
       "5               2  \n",
       "6               2  \n",
       "7               2  \n",
       "8               1  \n",
       "9               2  \n",
       "10              2  \n",
       "11              2  \n",
       "12              2  \n",
       "13              2  \n",
       "14              2  \n",
       "15              2  \n",
       "16              2  \n",
       "17              2  \n",
       "18              2  \n",
       "19              2  \n",
       "20              2  \n",
       "21              2  \n",
       "22              1  \n",
       "23              2  \n",
       "24              2  \n",
       "25              2  \n",
       "26              2  \n",
       "27              2  \n",
       "28              2  \n",
       "29              2  \n",
       "...           ...  \n",
       "207670          2  \n",
       "207671          1  \n",
       "207672          2  \n",
       "207673          2  \n",
       "207674          2  \n",
       "207675          2  \n",
       "207676          1  \n",
       "207677          2  \n",
       "207678          1  \n",
       "207679          2  \n",
       "207680          2  \n",
       "207681          2  \n",
       "207682          2  \n",
       "207683          2  \n",
       "207684          2  \n",
       "207685          2  \n",
       "207686          2  \n",
       "207687          2  \n",
       "207688          1  \n",
       "207689          2  \n",
       "207690          2  \n",
       "207691          2  \n",
       "207692          1  \n",
       "207693          1  \n",
       "207694          2  \n",
       "207695          2  \n",
       "207696          1  \n",
       "207697          2  \n",
       "207698          2  \n",
       "207699          2  \n",
       "\n",
       "[207700 rows x 19 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# 指定工作目录路径\n",
    "os.chdir('D:\\迁移率')\n",
    "data = pd.read_csv('qianyilv0911.csv',low_memory=False)\n",
    "data1 = data.drop(columns='记录数')\n",
    "data=data1.copy()\n",
    "name = list(data)\n",
    "# 把列名转为大写\n",
    "for n in name:\n",
    "#     print(n.upper())\n",
    "    data.rename(columns={n:n.upper()},inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-24T07:22:04.422172Z",
     "start_time": "2019-09-24T07:16:36.111000Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "迁移率数据写入完成！文件位置:D:\\迁移率\n"
     ]
    }
   ],
   "source": [
    "\n",
    "grant =['ZHONGAN' ,'ZHAOLIAN' ,'MASHANGXIAOJIN' ,'WEIXIN' ,'ZIZHUSHOUXIN' ,'BESTPAY' ,'GUOFU',\n",
    "       'DUMIAO' ,'FENQICHAOREN' ,'ZIYING' ,'TIANCHENGRONGZU']\n",
    "user =[1, 2, 3, 4, 5, 10]\n",
    "area = [\"广东省\", \"江苏省\", \"重庆市\", \"四川省\", \"新疆维吾尔自治区\", \"浙江省\", \"内蒙古自治区\", \"湖北省\", \"辽宁省\"]\n",
    "\n",
    "\n",
    "# 计算逾期期数\n",
    "# x:series y:账期数\n",
    "def overdue_num(x, y):\n",
    "    o_num = 0\n",
    "    for i in range(5, y + 1):\n",
    "        o_num = o_num + int(x['STATUS' + str(i)] == 'OPEN') + int(\n",
    "            x['REPAY_TIME' + str(i)] >= pd.to_datetime('2019-' + str(y) + '-11'))\n",
    "    return o_num\n",
    "\n",
    "\n",
    "for i in grant:\n",
    "    for j in user:\n",
    "        for k in area:\n",
    "            all = data.loc[(data['CREDIT_BY'] == i) & (data['USER_TYPE'] == j) & (data['ACCEPT_AREA_NAME'] == k)].copy()\n",
    "            if all.shape[0] == 0:\n",
    "                pass\n",
    "            else:\n",
    "                #                 print(all.shape)\n",
    "\n",
    "                # 转换时间\n",
    "                # all['REPAY_TIME4']=pd.to_datetime(all.REPAY_TIME4,format='%Y-%m-%d')\n",
    "                all['REPAY_TIME5'] = pd.to_datetime(all.REPAY_TIME5, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME6'] = pd.to_datetime(all.REPAY_TIME6, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME7'] = pd.to_datetime(all.REPAY_TIME7, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME8'] = pd.to_datetime(all.REPAY_TIME8, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME9'] = pd.to_datetime(all.REPAY_TIME9, format='%Y-%m-%d')\n",
    "                all['COMPLETE_TIME'] = pd.to_datetime(all.COMPLETE_TIME, format='%Y-%m-%d').dt.month\n",
    "                # 按完成时间分类\n",
    "                m4 = all[all['COMPLETE_TIME'] == 4]\n",
    "                m5 = all[all['COMPLETE_TIME'] == 5]\n",
    "                m6 = all[all['COMPLETE_TIME'] == 6]\n",
    "                m7 = all[all['COMPLETE_TIME'] == 7]\n",
    "                m8 = all[all['COMPLETE_TIME'] == 8]\n",
    "                m9 = all[all['COMPLETE_TIME'] == 9]\n",
    "                # 4月\n",
    "                # 按mob分类\n",
    "                # 4月完成\n",
    "                list_all_c_4 = list(m4['ACCOUNT_ID'])\n",
    "                # 5月\n",
    "                # 按mob分类\n",
    "                # 4月完成\n",
    "                list_m4_t_5 = list(m4[m4['STATUS5'] == 'TERMINATE']['ACCOUNT_ID']) + list(\n",
    "                    m4[m4['STATUS5'] == 'CLOSE']['ACCOUNT_ID'])\n",
    "                list_m4_m1_5 = list(m4[m4['STATUS5'] == 'OPEN']['ACCOUNT_ID']) + list(\n",
    "                    m4[m4['REPAY_TIME5'] >= '2019-5-11']['ACCOUNT_ID'])\n",
    "                list_m4_c_5 = list(set(m4['ACCOUNT_ID']) ^ set(list_m4_t_5 + list_m4_m1_5))\n",
    "\n",
    "                # 总的\n",
    "                list_all_t_5 = list_m4_t_5\n",
    "                list_all_m1_5 = list_m4_m1_5\n",
    "\n",
    "                list_all_c_5 = list_m4_c_5 + list(m5['ACCOUNT_ID'])\n",
    "\n",
    "                # 6月\n",
    "                # 取4月和五月完成的数据\n",
    "                m4_5 = pd.concat([m4, m5], ignore_index=True)\n",
    "                if m4_5.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_5['overdue_num'] = m4_5.apply(lambda x: overdue_num(x=x, y=6), axis=1)\n",
    "                else:\n",
    "                    m4_5['overdue_num'] = 0\n",
    "                list_all_m1_6 = list(m4_5[m4_5['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_6 = list(m4_5[m4_5['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_c_6 = list(\n",
    "                    m4_5.loc[(m4_5['STATUS6'] == 'CLEAR') & (m4_5['REPAY_TIME6'] < '2019-6-11')]['ACCOUNT_ID']) + list(\n",
    "                    m6['ACCOUNT_ID'])\n",
    "\n",
    "                # 7月\n",
    "                # 取4-6月完成的数据\n",
    "                m4_6 = pd.concat([m4, m5, m6], ignore_index=True)\n",
    "                if m4_6.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_6['overdue_num'] = m4_6.apply(lambda x: overdue_num(x=x, y=7), axis=1)\n",
    "                else:\n",
    "                    m4_6['overdue_num'] = 0\n",
    "                list_all_m1_7 = list(m4_6[m4_6['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_7 = list(m4_6[m4_6['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_7 = list(m4_6[m4_6['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_c_7 = list(\n",
    "                    m4_6.loc[(m4_6['STATUS7'] == 'CLEAR') & (m4_6['REPAY_TIME7'] < '2019-7-11')]['ACCOUNT_ID']) + list(\n",
    "                    m7['ACCOUNT_ID'])\n",
    "\n",
    "                # 8月\n",
    "                # 取4-7月完成的数据\n",
    "                m4_7 = pd.concat([m4, m5, m6, m7], ignore_index=True)\n",
    "                if m4_7.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_7['overdue_num'] = m4_7.apply(lambda x: overdue_num(x=x, y=8), axis=1)\n",
    "                else:\n",
    "                    m4_7['overdue_num'] = 0\n",
    "                list_all_m1_8 = list(m4_7[m4_7['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_8 = list(m4_7[m4_7['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_8 = list(m4_7[m4_7['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_8 = list(m4_7[m4_7['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_c_8 = list(\n",
    "                    m4_7.loc[(m4_7['STATUS8'] == 'CLEAR') & (m4_7['REPAY_TIME8'] < '2019-8-11')]['ACCOUNT_ID']) + list(\n",
    "                    m8['ACCOUNT_ID'])\n",
    "\n",
    "                # 9月\n",
    "                # 取4-8月完成的数据\n",
    "                m4_8 = pd.concat([m4, m5, m6, m7, m8], ignore_index=True)\n",
    "                if m4_8.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_8['overdue_num'] = m4_8.apply(lambda x: overdue_num(x=x, y=9), axis=1)\n",
    "                else:\n",
    "                    m4_8['overdue_num'] = 0\n",
    "                list_all_m1_9 = list(m4_8[m4_8['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_9 = list(m4_8[m4_8['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_9 = list(m4_8[m4_8['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_9 = list(m4_8[m4_8['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_m5_9 = list(m4_8[m4_8['overdue_num'] == 5]['ACCOUNT_ID'])\n",
    "                list_all_c_9 = list(\n",
    "                    m4_8.loc[(m4_8['STATUS9'] == 'CLEAR') & (m4_8['REPAY_TIME9'] < '2019-9-11')]['ACCOUNT_ID']) + list(\n",
    "                    m9['ACCOUNT_ID'])\n",
    "\n",
    "                # 计算结果保存\n",
    "                # C-M1\n",
    "                c_m1_05_z = len(set(list_all_m1_5) & set(list_all_c_4))\n",
    "                c_m1_05_m = len(list_all_c_4)\n",
    "                c_m1_06_z = len(set(list_all_m1_6) & set(list_all_c_5))\n",
    "                c_m1_06_m = len(list_all_c_5)\n",
    "                c_m1_07_z = len(set(list_all_m1_7) & set(list_all_c_6))\n",
    "                c_m1_07_m = len(list_all_c_6)\n",
    "                c_m1_08_z = len(set(list_all_m1_8) & set(list_all_c_7))\n",
    "                c_m1_08_m = len(list_all_c_7)\n",
    "                c_m1_09_z = len(set(list_all_m1_9) & set(list_all_c_8))\n",
    "                c_m1_09_m = len(list_all_c_8)\n",
    "\n",
    "                # M1-M2\n",
    "                m1_m2_06_z = len(set(list_all_m2_6) & set(list_all_m1_5))\n",
    "                m1_m2_06_m = len(list_all_m1_5)\n",
    "                m1_m2_07_z = len(set(list_all_m2_7) & set(list_all_m1_6))\n",
    "                m1_m2_07_m = len(list_all_m1_6)\n",
    "                m1_m2_08_z = len(set(list_all_m2_8) & set(list_all_m1_7))\n",
    "                m1_m2_08_m = len(list_all_m1_7)\n",
    "                m1_m2_09_z = len(set(list_all_m2_9) & set(list_all_m1_8))\n",
    "                m1_m2_09_m = len(list_all_m1_8)\n",
    "\n",
    "                # M2-M3\n",
    "                m2_m3_07_z = len(set(list_all_m3_7) & set(list_all_m2_6))\n",
    "                m2_m3_07_m = len(list_all_m2_6)\n",
    "                m2_m3_08_z = len(set(list_all_m3_8) & set(list_all_m2_7))\n",
    "                m2_m3_08_m = len(list_all_m2_7)\n",
    "                m2_m3_09_z = len(set(list_all_m3_9) & set(list_all_m2_8))\n",
    "                m2_m3_09_m = len(list_all_m2_8)\n",
    "\n",
    "                # M3-M4\n",
    "                m3_m4_08_z = len(set(list_all_m4_8) & set(list_all_m3_7))\n",
    "                m3_m4_08_m = len(list_all_m3_7)\n",
    "                m3_m4_09_z = len(set(list_all_m4_9) & set(list_all_m3_8))\n",
    "                m3_m4_09_m = len(list_all_m3_8)\n",
    "\n",
    "                # M4-M5\n",
    "                m4_m5_09_z = len(set(list_all_m5_9) & set(list_all_m4_8))\n",
    "                m4_m5_09_m = len(list_all_m4_8)\n",
    "\n",
    "                # C-M2\n",
    "                c_m2_06_z = c_m1_05_z * m1_m2_06_z\n",
    "                c_m2_06_m = c_m1_05_m * m1_m2_06_m\n",
    "                c_m2_07_z = c_m1_06_z * m1_m2_07_z\n",
    "                c_m2_07_m = c_m1_06_m * m1_m2_07_m\n",
    "                c_m2_08_z = c_m1_07_z * m1_m2_08_z\n",
    "                c_m2_08_m = c_m1_07_m * m1_m2_08_m\n",
    "                c_m2_09_z = c_m1_08_z * m1_m2_09_z\n",
    "                c_m2_09_m = c_m1_08_m * m1_m2_09_m\n",
    "\n",
    "                # C-M3\n",
    "                c_m3_07_z = c_m1_05_z * m1_m2_06_z * m2_m3_07_z\n",
    "                c_m3_07_m = c_m1_05_m * m1_m2_06_m * m2_m3_07_m\n",
    "                c_m3_08_z = c_m1_06_z * m1_m2_07_z * m2_m3_08_z\n",
    "                c_m3_08_m = c_m1_06_m * m1_m2_07_m * m2_m3_08_m\n",
    "                c_m3_09_z = c_m1_07_z * m1_m2_08_z * m2_m3_09_z\n",
    "                c_m3_09_m = c_m1_07_m * m1_m2_08_m * m2_m3_09_m\n",
    "\n",
    "                # C-M4\n",
    "                c_m4_08_z = c_m1_05_z * m1_m2_06_z * m2_m3_07_z * m3_m4_08_z\n",
    "                c_m4_08_m = c_m1_05_m * m1_m2_06_m * m2_m3_07_m * m3_m4_08_m\n",
    "                c_m4_09_z = c_m1_06_z * m1_m2_07_z * m2_m3_08_z * m3_m4_09_z\n",
    "                c_m4_09_m = c_m1_06_m * m1_m2_07_m * m2_m3_08_m * m3_m4_09_m\n",
    "\n",
    "                # C-M5\n",
    "                c_m5_09_z = c_m1_05_z * m1_m2_06_z * m2_m3_07_z * m3_m4_08_z * m4_m5_09_z\n",
    "                c_m5_09_m = c_m1_05_m * m1_m2_06_m * m2_m3_07_m * m3_m4_08_m * m4_m5_09_m\n",
    "\n",
    "                # C-C\n",
    "                c_c_05_z = len(set(list_all_c_4) & set(list_all_c_5))\n",
    "                c_c_05_m = len(set(list_all_c_4))\n",
    "                c_c_06_z = len(set(list_all_c_6) & set(list_all_c_5))\n",
    "                c_c_06_m = len(set(list_all_c_5))\n",
    "                c_c_07_z = len(set(list_all_c_7) & set(list_all_c_6))\n",
    "                c_c_07_m = len(set(list_all_c_6))\n",
    "                c_c_08_z = len(set(list_all_c_8) & set(list_all_c_7))\n",
    "                c_c_08_m = len(set(list_all_c_7))\n",
    "                c_c_09_z = len(set(list_all_c_9) & set(list_all_c_8))\n",
    "                c_c_09_m = len(set(list_all_c_8))\n",
    "\n",
    "                # M1-C\n",
    "                m1_c_06_z = len(set(list_all_m1_5) & set(list_all_c_6))\n",
    "                m1_c_06_m = len(set(list_all_m1_5))\n",
    "                m1_c_07_z = len(set(list_all_m1_6) & set(list_all_c_7))\n",
    "                m1_c_07_m = len(set(list_all_m1_6))\n",
    "                m1_c_08_z = len(set(list_all_m1_7) & set(list_all_c_8))\n",
    "                m1_c_08_m = len(set(list_all_m1_7))\n",
    "                m1_c_09_z = len(set(list_all_m1_8) & set(list_all_c_9))\n",
    "                m1_c_09_m = len(set(list_all_m1_8))\n",
    "\n",
    "                # M2-C\n",
    "\n",
    "                m2_c_07_z = len(set(list_all_m2_6) & set(list_all_c_7))\n",
    "                m2_c_07_m = len(list_all_m2_6)\n",
    "                m2_c_08_z = len(set(list_all_m2_7) & set(list_all_c_8))\n",
    "                m2_c_08_m = len(list_all_m2_7)\n",
    "                m2_c_09_z = len(set(list_all_m2_8) & set(list_all_c_9))\n",
    "                m2_c_09_m = len(list_all_m2_8)\n",
    "\n",
    "                # M3-C\n",
    "                m3_c_08_z = len(set(list_all_m3_7) & set(list_all_c_8))\n",
    "                m3_c_08_m = len(list_all_m3_7)\n",
    "                m3_c_09_z = len(set(list_all_m3_8) & set(list_all_c_9))\n",
    "                m3_c_09_m = len(list_all_m3_8)\n",
    "\n",
    "                # M4-C\n",
    "                m4_c_09_z = len(set(list_all_m4_8) & set(list_all_c_9))\n",
    "                m4_c_09_m = len(list_all_m4_8)\n",
    "                \n",
    "                # M1-M1\n",
    "                m1_m1_06_z = len(set(list_all_m1_6) & set(list_all_m1_5))\n",
    "                m1_m1_06_m = len(set(list_all_m1_5))\n",
    "                m1_m1_07_z = len(set(list_all_m1_7) & set(list_all_m1_6))\n",
    "                m1_m1_07_m = len(set(list_all_m1_6))\n",
    "                m1_m1_08_z = len(set(list_all_m1_8) & set(list_all_m1_7))\n",
    "                m1_m1_08_m = len(set(list_all_m1_7))\n",
    "                m1_m1_09_z = len(set(list_all_m1_9) & set(list_all_m1_8))\n",
    "                m1_m1_09_m = len(set(list_all_m1_8))\n",
    "\n",
    "                # M2-M1\n",
    "                m2_m1_07_z = len(set(list_all_m2_6) & set(list_all_m1_7))\n",
    "                m2_m1_07_m = len(set(list_all_m2_6))\n",
    "                m2_m1_08_z = len(set(list_all_m2_7) & set(list_all_m1_8))\n",
    "                m2_m1_08_m = len(set(list_all_m2_7))\n",
    "                m2_m1_09_z = len(set(list_all_m2_8) & set(list_all_m1_9))\n",
    "                m2_m1_09_m = len(set(list_all_m2_8))\n",
    "\n",
    "                # M3-M1\n",
    "                m3_m1_08_z = len(set(list_all_m3_7) & set(list_all_m1_8))\n",
    "                m3_m1_08_m = len(list_all_m3_7)\n",
    "                m3_m1_09_z = len(set(list_all_m3_8) & set(list_all_m1_9))\n",
    "                m3_m1_09_m = len(list_all_m3_8)\n",
    "\n",
    "                # M4-M1\n",
    "                m4_m1_09_z = len(set(list_all_m4_8) & set(list_all_m1_9))\n",
    "                m4_m1_09_m = len(list_all_m4_8)\n",
    "                \n",
    "\n",
    "                # 数据写入到文件\n",
    "                with open('迁移率(10号)导出V2.0.txt', 'a+') as f:\n",
    "                    # C-M1\n",
    "                    c_m1_5 = \"{},{},{},C-M1,201905,{},{}\".format(i, j, k, c_m1_05_z, c_m1_05_m)\n",
    "                    c_m1_6 = \"{},{},{},C-M1,201906,{},{}\".format(i, j, k, c_m1_06_z, c_m1_06_m)\n",
    "                    c_m1_7 = \"{},{},{},C-M1,201907,{},{}\".format(i, j, k, c_m1_07_z, c_m1_07_m)\n",
    "                    c_m1_8 = \"{},{},{},C-M1,201908,{},{}\".format(i, j, k, c_m1_08_z, c_m1_08_m)\n",
    "                    c_m1_9 = \"{},{},{},C-M1,201909,{},{}\".format(i, j, k, c_m1_09_z, c_m1_09_m)\n",
    "                    f.write(c_m1_5 + '\\n' + c_m1_6 + '\\n' + c_m1_7 + '\\n' + c_m1_8 + '\\n' + c_m1_9 + '\\n')\n",
    "\n",
    "                    # M1-M2\n",
    "                    m1_m2_6 = \"{},{},{},M1-M2,201906,{},{}\".format(i, j, k, m1_m2_06_z, m1_m2_06_m)\n",
    "                    m1_m2_7 = \"{},{},{},M1-M2,201907,{},{}\".format(i, j, k, m1_m2_07_z, m1_m2_07_m)\n",
    "                    m1_m2_8 = \"{},{},{},M1-M2,201908,{},{}\".format(i, j, k, m1_m2_08_z, m1_m2_08_m)\n",
    "                    m1_m2_9 = \"{},{},{},M1-M2,201909,{},{}\".format(i, j, k, m1_m2_09_z, m1_m2_09_m)\n",
    "\n",
    "                    f.write(m1_m2_6 + '\\n' + m1_m2_7 + '\\n' + m1_m2_8 + '\\n' + m1_m2_9 + '\\n')\n",
    "\n",
    "                    # M2-M3\n",
    "                    m2_m3_7 = \"{},{},{},M2-M3,201907,{},{}\".format(i, j, k, m2_m3_07_z, m2_m3_07_m)\n",
    "                    m2_m3_8 = \"{},{},{},M2-M3,201908,{},{}\".format(i, j, k, m2_m3_08_z, m2_m3_08_m)\n",
    "                    m2_m3_9 = \"{},{},{},M2-M3,201909,{},{}\".format(i, j, k, m2_m3_09_z, m2_m3_09_m)\n",
    "\n",
    "                    f.write(m2_m3_7 + '\\n' + m2_m3_8 + '\\n' + m2_m3_9 + '\\n')\n",
    "\n",
    "                    # M3-M4\n",
    "                    m3_m4_8 = \"{},{},{},M3-M4,201908,{},{}\".format(i, j, k, m3_m4_08_z, m3_m4_08_m)\n",
    "                    m3_m4_9 = \"{},{},{},M3-M4,201909,{},{}\".format(i, j, k, m3_m4_09_z, m3_m4_09_m)\n",
    "\n",
    "                    f.write(m3_m4_8 + '\\n' + m3_m4_9 + '\\n')\n",
    "\n",
    "                    # M4-M5\n",
    "                    m4_m5_9 = \"{},{},{},M4-M5,201909,{},{}\".format(i, j, k, m4_m5_09_z, m4_m5_09_m)\n",
    "\n",
    "                    f.write(m4_m5_9 + '\\n') \n",
    "\n",
    "                    # C-M2\n",
    "                    c_m2_6 = \"{},{},{},C-M2,201906,{},{}\".format(i, j, k, c_m2_06_z, c_m2_06_m)\n",
    "                    c_m2_7 = \"{},{},{},C-M2,201907,{},{}\".format(i, j, k, c_m2_07_z, c_m2_07_m)\n",
    "                    c_m2_8 = \"{},{},{},C-M2,201908,{},{}\".format(i, j, k, c_m2_08_z, c_m2_08_m)\n",
    "                    c_m2_9 = \"{},{},{},C-M2,201909,{},{}\".format(i, j, k, c_m2_09_z, c_m2_09_m)\n",
    "\n",
    "                    f.write(c_m2_6 + '\\n' + c_m2_7 + '\\n' + c_m2_8 + '\\n' + c_m2_9 + '\\n')\n",
    "\n",
    "                    # C-M3\n",
    "                    c_m3_7 = \"{},{},{},C-M3,201907,{},{}\".format(i, j, k, c_m3_07_z, c_m3_07_m)\n",
    "                    c_m3_8 = \"{},{},{},C-M3,201908,{},{}\".format(i, j, k, c_m3_08_z, c_m3_08_m)\n",
    "                    c_m3_9 = \"{},{},{},C-M3,201909,{},{}\".format(i, j, k, c_m3_09_z, c_m3_09_m)\n",
    "\n",
    "                    f.write(c_m3_7 + '\\n' + c_m3_8 + '\\n' + c_m3_9 + '\\n')\n",
    "\n",
    "                    # C-M4\n",
    "                    c_m4_8 = \"{},{},{},C-M4,201908,{},{}\".format(i, j, k, c_m4_08_z, c_m4_08_m)\n",
    "                    c_m4_9 = \"{},{},{},C-M4,201909,{},{}\".format(i, j, k, c_m4_09_z, c_m4_09_m)\n",
    "\n",
    "                    f.write(c_m4_8 + '\\n' + c_m4_9 + '\\n')\n",
    "\n",
    "                    # C-M5\n",
    "                    c_m5_9 = \"{},{},{},C-M5,201909,{},{}\".format(i, j, k, c_m5_09_z, c_m5_09_m)\n",
    "\n",
    "                    f.write(c_m5_9 + '\\n')\n",
    "                    \n",
    "                    # C-C\n",
    "                    c_c_5 = \"{},{},{},C-C,201905,{},{}\".format(i, j, k, c_c_05_z, c_c_05_m)\n",
    "                    c_c_6 = \"{},{},{},C-C,201906,{},{}\".format(i, j, k, c_c_06_z, c_c_06_m)\n",
    "                    c_c_7 = \"{},{},{},C-C,201907,{},{}\".format(i, j, k, c_c_07_z, c_c_07_m)\n",
    "                    c_c_8 = \"{},{},{},C-C,201908,{},{}\".format(i, j, k, c_c_08_z, c_c_08_m)\n",
    "                    c_c_9 = \"{},{},{},C-C,201909,{},{}\".format(i, j, k, c_c_09_z, c_c_09_m)\n",
    "                    f.write(c_c_5 + '\\n' + c_c_6 + '\\n' + c_c_7 + '\\n' + c_c_8 + '\\n' + c_c_9 + '\\n')\n",
    "\n",
    "                    # M1-C\n",
    "                    m1_c_6 = \"{},{},{},M1-C,201906,{},{}\".format(i, j, k, m1_c_06_z, m1_c_06_m)\n",
    "                    m1_c_7 = \"{},{},{},M1-C,201907,{},{}\".format(i, j, k, m1_c_07_z, m1_c_07_m)\n",
    "                    m1_c_8 = \"{},{},{},M1-C,201908,{},{}\".format(i, j, k, m1_c_08_z, m1_c_08_m)\n",
    "                    m1_c_9 = \"{},{},{},M1-C,201909,{},{}\".format(i, j, k, m1_c_09_z, m1_c_09_m)\n",
    "\n",
    "                    f.write(m1_c_6 + '\\n' + m1_c_7 + '\\n' + m1_c_8 + '\\n' + m1_c_9 + '\\n')\n",
    "\n",
    "                    # M2-C\n",
    "                    m2_c_7 = \"{},{},{},M2-C,201907,{},{}\".format(i, j, k, m2_c_07_z, m2_c_07_m)\n",
    "                    m2_c_8 = \"{},{},{},M2-C,201908,{},{}\".format(i, j, k, m2_c_08_z, m2_c_08_m)\n",
    "                    m2_c_9 = \"{},{},{},M2-C,201909,{},{}\".format(i, j, k, m2_c_09_z, m2_c_09_m)\n",
    "\n",
    "                    f.write(m2_c_7 + '\\n' + m2_c_8 + '\\n' + m2_c_9 + '\\n')\n",
    "\n",
    "                    # M3-C\n",
    "                    m3_c_8 = \"{},{},{},M3-C,201908,{},{}\".format(i, j, k, m3_c_08_z, m3_c_08_m)\n",
    "                    m3_c_9 = \"{},{},{},M3-C,201909,{},{}\".format(i, j, k, m3_c_09_z, m3_c_09_m)\n",
    "\n",
    "                    f.write(m3_c_8 + '\\n' + m3_c_9 + '\\n')\n",
    "\n",
    "                    # M4-C\n",
    "                    m4_c_9 = \"{},{},{},M4-C,201909,{},{}\".format(i, j, k, m4_c_09_z, m4_c_09_m)\n",
    "\n",
    "                    f.write(m4_c_9 + '\\n')\n",
    "                    \n",
    "                    # M1-M1\n",
    "                    m1_m1_6 = \"{},{},{},M1-M1,201906,{},{}\".format(i, j, k, m1_m1_06_z, m1_m1_06_m)\n",
    "                    m1_m1_7 = \"{},{},{},M1-M1,201907,{},{}\".format(i, j, k, m1_m1_07_z, m1_m1_07_m)\n",
    "                    m1_m1_8 = \"{},{},{},M1-M1,201908,{},{}\".format(i, j, k, m1_m1_08_z, m1_m1_08_m)\n",
    "                    m1_m1_9 = \"{},{},{},M1-M1,201909,{},{}\".format(i, j, k, m1_m1_09_z, m1_m1_09_m)\n",
    "\n",
    "                    f.write(m1_m1_6 + '\\n' + m1_m1_7 + '\\n' + m1_m1_8 + '\\n' + m1_m1_9 + '\\n')\n",
    "\n",
    "                    # M2-M1\n",
    "                    m2_m1_7 = \"{},{},{},M2-M1,201907,{},{}\".format(i, j, k, m2_m1_07_z, m2_m1_07_m)\n",
    "                    m2_m1_8 = \"{},{},{},M2-M1,201908,{},{}\".format(i, j, k, m2_m1_08_z, m2_m1_08_m)\n",
    "                    m2_m1_9 = \"{},{},{},M2-M1,201909,{},{}\".format(i, j, k, m2_m1_09_z, m2_m1_09_m)\n",
    "\n",
    "                    f.write(m2_m1_7 + '\\n' + m2_m1_8 + '\\n' + m2_m1_9 + '\\n')\n",
    "\n",
    "                    # M3-M1\n",
    "                    m3_m1_8 = \"{},{},{},M3-M1,201908,{},{}\".format(i, j, k, m3_m1_08_z, m3_m1_08_m)\n",
    "                    m3_m1_9 = \"{},{},{},M3-M1,201909,{},{}\".format(i, j, k, m3_m1_09_z, m3_m1_09_m)\n",
    "\n",
    "                    f.write(m3_m1_8 + '\\n' + m3_m1_9 + '\\n')\n",
    "\n",
    "                    # M4-M1\n",
    "                    m4_m1_9 = \"{},{},{},M4-M1,201909,{},{}\".format(i, j, k, m4_m1_09_z, m4_m1_09_m)\n",
    "\n",
    "                    f.write(m4_m1_9 + '\\n')\n",
    "                    \n",
    "print('迁移率数据写入完成！文件位置:{}'.format(os.getcwd()))"
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